Averages Bowling - vs Bangladesh

Bowling Averages for List A in the 2017 - vs Bangladesh

Bowling averages
Player
Span
Mat
Inns
Balls
Mdns
Runs
Wkts
BBI
Ave
Econ
SR
5
10
Ct
St
MM Ali2017-20171148140---5.00-----
HM Amla2017-20172-0---------2-
CJ Anderson2017-20172248-56---7.00---1-
R Ashwin2017-20171160-54---5.40-----
A Balbirnie2017-20172-0-----------
JT Ball2017-2017116018211/8282.008.2060.0----
T Bavuma2017-20171-0-----------
F Behardien2017-20172-0---------1-
HK Bennett2017-20172211617843/3119.504.0329.0--1-
TA Boult2017-20171160-4811/4848.004.8060.0----
NT Broom2017-20173-0-----------
JJ Bumrah2017-2017116013922/3919.503.9030.0--1-
JC Buttler2017-20171-0---------1-
LD Chandimal2017-20173-0---------31
PKD Chase2017-20172278-8833/3329.336.7626.0----
PJ Cummins2017-2017114812211/2222.002.7548.0----
Q de Kock2017-20173-0---------4-
AB de Villiers2017-20173-0---------2-
S Dhawan2017-20171-0-----------
MS Dhoni2017-20171-0---------1-
GH Dockrell2017-20172260-44---4.40---1-
JP Duminy2017-2017216-8---8.00---1-
F du Plessis2017-20173-0---------2-
N Pradeep2017-20171-0-----------
AJ Finch2017-20171-0---------1-
DAS Gunaratne2017-20173272-5611/4056.004.6672.0--1-
MD Gunathilaka2017-20173118-22---7.33---2-
MJ Guptill2017-20171-0-----------
AD Hales2017-20171-0---------1-
JR Hazlewood2017-20171160-4011/4040.004.0060.0--1-
TM Head2017-20171148-3311/3333.004.1248.0----
MC Henriques2017-20171130-3011/3030.006.0030.0----
MJ Henry2017-20171160-49---4.90-----
Imran Tahir2017-201733172112263/5020.334.2528.6----
RA Jadeja2017-20171160-4811/4848.004.8060.0--1-
KM Jadhav2017-20171136-2222/2211.003.6618.0----
EC Joyce2017-20171-0-----------
V Kohli2017-20171-0---------1-
KMDN Kulasekara2017-20172145-3744/379.254.9311.2--1-
B Kumar2017-2017116015322/5326.505.3030.0----
CBRLS Kumara2017-20171148-7411/7474.009.2548.0----
RAS Lakmal2017-20173296-8342/3820.755.1824.0----
TWM Latham2017-20172-0---------1-
AK Markram2017-20171118-1822/189.006.009.0--1-
GJ Maxwell2017-2017116-9---9.00-----
BJ McCarthy2017-20172260-8521/4242.508.5030.0----
BKG Mendis2017-20173-0-----------
DA Miller2017-20171-0---------1-
AF Milne2017-20171156-5811/5858.006.2156.0----
EJG Morgan2017-20171-0-----------
PWA Mulder2017-20171148-3211/3232.004.0048.0----
C Munro2017-20172112-14---7.00---1-
TJ Murtagh2017-20172273149---4.02---1-
JDS Neesham2017-201733102-12622/6863.007.4151.0--1-
KJ O'Brien2017-20172243-3411/2234.004.7443.0----
NJ O'Brien2017-20172-0---------3-
HH Pandya2017-20171124-34---8.50-----
JS Patel2017-20171160-5522/5527.505.5030.0----
D Paterson2017-201733161-18043/4445.006.7040.2--2-
SS Pathirana2017-20171130-27---5.40-----
MDK Perera2017-2017216014722/4723.504.7030.0----
NLTC Perera2017-20173260-77---7.70-----
AL Phehlukwayo2017-201733144211354/4022.604.7028.8----
LE Plunkett2017-20171160-5944/5914.755.9015.0----
WTS Porterfield2017-20172-0-----------
S Prasanna2017-2017116013322/3316.503.3030.0--1-
D Pretorius2017-201722120-9642/4824.004.8030.0----
K Rabada2017-201733162311654/4323.204.2932.4--1-
SHA Rance2017-20171154-66---7.33---3-
L Ronchi2017-20173-0---------2-
JE Root2017-20171118-18---6.00-----
JJ Roy2017-20171-0---------1-
PADLR Sandakan2017-20171148-4311/4343.005.3748.0--2-
MJ Santner2017-201733180113621/3668.004.5390.0--1-
RG Sharma2017-20171-0-----------
TAM Siriwardana2017-20173130123---4.60-----
SPD Smith2017-20171-0---------1-
IS Sodhi2017-2017116014022/4020.004.0030.0----
TG Southee2017-2017115414533/4515.005.0018.0----
MA Starc2017-2017115122944/297.253.4112.7----
PR Stirling2017-20172112-14---7.00-----
BA Stokes2017-20171142-4211/4242.006.0042.0--1-
LRPL Taylor2017-20173-0-----------
WU Tharanga2017-20173-0---------2-
SR Thompson2017-20171124-19---4.75-----
MS Wade2017-20171-0---------1-
DA Warner2017-20171-0-----------
KS Williamson2017-20171112-19---9.50-----
GC Wilson2017-20172-0---------1-
CR Woakes2017-2017111214---2.00-----
MA Wood2017-20171160158---5.80---1-
GH Worker2017-20171-0-----------
Yuvraj Singh2017-20171-0-----------
A Zampa2017-2017112411322/136.503.2512.0----
Adjust:Most recentPast weekPast MonthPast year4 years10 years25 years
Performances in matches that overlap years are credited to the year in which they occurred - this results in some unknown data, especially in regard to bowling figures